Majid Sarvi

Chair of Transport Engineering
Professor in Transport for Smart Cities
The University of Melbourne


Majid Sarvi is the chair in Transport Engineering, the professor in Transport for Smart Cities and the program director of the "Transport Technologies" at the University of Melbourne. He is the founder and the director of the AIMES (Australian Integrated Multimodal EcoSystem). AIMES is the world’s first and largest connected urban testing ecosystem for implementing and testing of emerging connected transport technologies at large scale and in complex urban environments which involves over 40 partners from government and leading Australian and global industry partners.

He has over 23 years of professional, academic and research experience in the areas of traffic and transport engineering. His research is multidisciplinary with international outlook and both theoretically oriented and applied in nature. His fields of research cover a range of topics, including: connected multimodal transport network , crowd dynamic modelling and simulation and network vulnerability assessment and optimization. He has been the author/co-author of over 250 refereed publications in top transportation journals and various conference and symposia proceedings. He currently serves on the editorial board of several journals including Transportation Research Part B, Transportation Research Part C, Transportmetrica, and Journal of Transportation Letters.

He has served on several international research committees, the Network Modelling Committee (ADB30), Traffic Flow Theory and Characteristics Committee (AHB45), and the Emergency Evacuation Committee (ABR30) of the Transportation Research Board (TRB) of the U.S. National Research Council. He is also the co-founder and co-chair of the Crowd Dynamic Modelling Subcommittee AHB45(2) of TRB.

Australian Integrated Multimodal EcoSystem (AIMES)

The AIMES includes a network of diverse intelligent and distributed sensors that is used to study, test and deploy a variety of innovative connected transport technologies. The ecosystem exploits the potential for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication systems by testing new applications and deploying effective technologies into vehicle fleets and infrastructure/assets. The AIMES focuses on the multimodal transport system consisting of connected vehicles and roadways, connected freight and city logistics, connected public transport, connected pedestrians and cyclists and smart public transport stations. It is the world’s first and largest connected urban laboratory for implementing and testing of emerging connected transport technologies at a large scale and in a complex urban environment.

Industry and Government Partners:

PTV GROUP, CUBIC, VicRoads, Public Transport Victoria (PTV), DEDJTR, TAC, City of Melbourne, City of Yarra, WSP, Telstra, HERE Maps, CISCO, Ericsson, nbn, Siemens, Toshiba, ITS-Australia, Transdev, EastLink, Yarra Tram, IAG, RACV, Q-free, Cohda Wireless, Kapsch, Scania, HMI technologies, Philips, NordicBuilt, Easymile, AEV, Bestrane, Woolworth, Local Motors, Deep Recognition.

Connected Multimodal Transport Network Modelling and Analysis

This research focuses on connected multimodal transport network modelling, transport network optimisation, and land use and transport interaction modelling. The utilisation of live data, sensor network, crowdsourcing and technology are the main foundation of this research. We use complex network theory, predictive modelling, machine learning, big data analysis and sophisticated mathematical modelling and optimisation to analyse large multimodal transport networks from operation to management and planning. As part of this research theme, we also study road transport network resiliency and vulnerability. The outcome will be used to reduce traffic congestion, improve safety and enhance the sustainability of transport system.

Crowd Dynamics Modelling and Simulations

Pedestrian crowd safety is an important matter as there have been numerous incidents in which crowd panic has resulted in severe injuries and death. This research focuses on crowd dynamic modelling, experiments and simulation during extreme emergency and panic. This work will enable the development of modelling tools which can be used in the planning, design, and management of major gathering and public places. These tools can also be used in a wide range of applications such as designing of major infrastructures, assisting disaster relief agencies and police wherever crowd movement is a central concern. In this work to study crowd dynamic under panic we blend empirical data collected from human crowd under normal walking conditions and group behaviour of live biological organisms (ants, woodlice, and mice) experimentation under panic conditions.


Please See Google Scholar for most up to date publications.

Research Fellows:

Milad Haghani

Crowd dynamics & route choice behaviour of crowds.

Saeed Asadi

Large transport network modelling and optimisation.

Benny Chen

Infrastructure resilience in large disaster events.

Research Associates:

Liam Scanlon

Software engineer & crowd dynamics researcher.

Current PhD Students:

Zahra Shahosseini

The impact of architecture on collective and individual behaviour during normal & emergency evacuation.

Arash Kaviani

Transportation network resilience quantification and optimisation.

Yan Li

Crowd dynamics, smart stations & image processing.

Azadeh Emami

Multimodal traffic signal control in connected transport networks.

Abdulla Alhawsawi

Crowd dynamics.

Former PhD Students:

Keyvan Aghabeyk

Amir Sobhani

Hassan Sabzeali

Mahmoud Mesbah

Sara Moridpour

Ali Zavabeti

Nirajan Shiwakoti

Md Aftabuzzaman

Ruimin Li

Kelvin Goh

Milad Haghani

Saeed Asadi

Katerina Pavkova

Long Troung

Farhana Nazanin

Charita Dias


I have several PhD positions and looking for creative an talented students good at maths, computer programming and optimisation. Students from civil engineering, transport engineering, applied and pure mathematics and physics, computer programming and computer vision, electrical engineering, and operation researches are welcome to apply. For further information contact me through my email address.